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Blog Posts
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GeoGSBPM: A framework for integrating geospatial data within the statistical process
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18 Jun, 2024
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Unlocking the Power of Geospatial Data with GIS Data Integration: A New R Package
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14 Feb, 2024
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The UN Integrated Geospatial Information Framework - Strengthening geospatial information management
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29 Jan, 2024
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The Global Statistical Geospatial Framework - A framework for the world
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29 Nov, 2023
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The low-down on the Joint Workshop on Integrating Statistical and Geospatial Information
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23 Oct, 2023
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UNECE Survey - Part 4: Issues and Obstacles
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18 Aug, 2023
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UNECE Survey - Part 3: Collaboration and Partnerships
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17 Aug, 2023
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UNECE Survey - Part 2: Data and Technology
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07 Aug, 2023
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UNECE Survey - Part 1: Background and Context
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02 Aug, 2023
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Data Integration: Key players and recent developments
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17 Jul, 2023
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Welcome to INGEST, our new blog series on integrating geospatial and statistical data
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03 Jul, 2023
UNECE and the modernisation of official statistics
Before we dive into the detail of the GeoGSBPM, it is useful to set the framework within its wider context and look at UNECE's role within the modernisation of official statistics. UNECE's Statistical Division plays a leading role in coordinating statistical activities across the UNECE region, particularly helping countries to strengthen, modernise and harmonise their statistical systems under the guidance of the Fundamental Principles of Official Statistics. The Division works with networks of experts to create statistical guidelines, recommendations and standards that are at the forefront of the discipline and have a global reach.
Of importance, the High-Level Group for the Modernisation of Official Statistics (HLG-MOS) was formed by the Conference of European Statisticians as a forum to drive the modernisation of official statistics in areas such as big data, machine learning and strategic communication. It consists of Chief Statisticians from national and international organisations who lead the implementation of new methods, technologies and other capabilities in statistical organisations. UNECE works with the HLG-MOS to create, implement and enhance standards for statistical production, with a particular focus on standards for metadata. In doing so, this ensures that “common definitions and processes are used within and between statistical organisations, helping to remove the barriers to collaboration on technical projects, fostering the sharing of knowledge and experiences, and serving as a basis for streamlined statistical production” (UNECE).
The cornerstones of the standards-based modernisation vision of HLG-MOS is a set of "ModernStats models" which includes the Generic Activity Model for Statistical Organisations (GAMSO), Generic Statistical Business Process Model (GSBPM) and Generic Statistical Information Model (GSIM).
Among these models, the GSBPM is the most widely implemented across the statistical organisations around the world, providing a standard framework as well as harmonised terminology that guides organisations as they modernise their production processes. The model consists of eight overarching processes (or phases) which are supported by a range of underlying sub-processes which are shown in the diagram to the right. As a model extensively used globally, the GSBPM is an optimal vehicle to incorporate the essential considerations and activities needed for geospatially-enabled statistics within the production process.
The HLG-MOS wiki site also contains a wealth of information on the activities, meetings and outcomes of the group, including detailed documentation, support and guidance on the standards-based models that they have helped to produce.
The Generic Statistical Business Process Model (Source: UNECE)
A geospatial view of the Generic Statistical Business Process Model (GeoGSBPM)
UNECE published the Geospatial View of the Generic Statistical Business Process Model (GeoGSBPM) in 2021 in recognition of the increasingly important role that geospatial information plays in the activities of statistical organisations and the production of geospatially-enabled statistics that are crucial to understanding (and addressing) some of the biggest challenges we face, such as the impacts of climate change, social inequality, and economic uncertainty. As such, they consider that "statistical organisations should be prepared to produce geospatially enabled statistical data in an efficient and timely manner . . . [and that] geospatially relevant activities and considerations should be integrated into the regular production processes of statistical organisations, so that the design and production of geospatially enabled statistics can be conducted in a systematic and consistent way" (UNECE). Hence, the GeoGSBPM was developed.
The GeoGSBPM emerged from a detailed review of the intersection of two important (and complementary) global frameworks: the Generic Statistical Business Process Model (GSBPM) (summarised in the previous section) and the Global Statistical Geospatial Framework (GSGF) (first published by UN-GGIM in 2019 as a key policy framework to support the production of high-quality harmonised and standardised geo-statistical data - you can find out more about this framework in one of our earlier blog posts).
The GSBPM has been described as "an enabling framework" (UNECE) for the overarching principles of the GSGF to be integrated within the statistical production process, providing a structure for all relevant geospatial activities to be undertaken across the correct stages of the process (see image to the right). The authors' also highlight the direct link between the GSBPM and Principle 4 of the GSGF, that of statistical and geospatial interoperability, however, its relevance is also evident across the other four GSGF principles.
Within the GeoGSBPM, the key activities to be undertaken to integrate geospatial and statistical data have been usefully summarised in a table which is structured according to GSGF Principle and GSBPM Phase. This provides a clear overview of the activities and considerations required across each stage of the statistical production process, each of which are then described in more detail in the following chapter (Geospatial related activities and considerations).
The intersection between the GSBPM and the GSGF (Source: UNECE)
As well as phase-specific activities and considerations, the GeoGSBPM also presents three overarching and corporate level activities which should be applied at an organisational level:
- Strategic collaboration and cooperation, to ensure that coordination and cooperation is maximised across the data ecosystem and its various stakeholders (which can span multiple organisations).
- Metadata management, by growing statistical awareness of the variety of metadata associated with geospatial datasets, identifying the core metadata elements required across the production process, as well as progressing the alignment of statistical and geospatial metadata concepts.
- Quality management, through the identification of authoritative sources of reference data, developing feedback mechanisms across the statistical and geospatial domains, developing suitable quality metrics, as well as horizon-scanning and monitoring developments in the geospatial field to ensure that activities are current and in harmony with other communities.
In carrying out these activities, statistical organisations can produce high-quality geo-statistical data that follows the principles of the GSGF.
How will the GeoGSBPM benefit me and my organisation?
Adopting the GeoGSBPM will bring many benefits, such as:
By adopting the GeoGSBPM, statistical organisations can produce geospatially enabled statistics in both a consistent and systematic way which will drive the greater harmonisation and interoperability of data across organisations, from the national to the global scale. It also provides an important feedback mechanism to improve the quality and accessibility of geospatial data. Crucially, the GeoGSBPM acts as a pillar which sets out the practical steps for integrating geospatial information within the statistical process, ensuring that the resulting data meets the high standards required to support data-driven decision-making and policy development across multiple spatial scales.
Looking ahead . . .
The INGEST blog series was established as part of an EU-funded project to develop greater capacity in the integration of statistical and geospatial information. Following the completion of this project, we are still keen to continue providing regular blog posts for INGEST. If you have an interesting project, concept, activity, or perspective that falls within the realms of statistical and geospatial data integration, we would love to hear from you! Please get in touch with Sara Stewart (UNECE Consultant) or Taeke Gjaltema (UNECE Regional Advisor for Statistics) to discuss this further. Until next time!
Acknowledgements: We are very grateful to InKyung Choi (UNECE) for contributing to this post.
Guest Authors: Hossein Hassani (Webster University, Vienna, Austria), Leila Marvian (Big Data Lab, Imam Reza International University, Mashhad 178-436, Iran) and Steve MacFeely (World Health Organisation)
Each dataset comes with its unique set of metadata, accuracy levels, and update cycles, necessitating a nuanced approach to integration. The process of ensuring compatibility and coherence across datasets involves not just simple data cleaning procedures but also sophisticated techniques like coordinate transformation, conflation, and the reconciliation of semantic differences. Moreover, the rapid evolution of technology and data acquisition methods means that geospatial datasets are expanding not only in size but also in complexity. Historically, the lack of standardised tools tailored to tackle these multifaceted tasks has been a bottleneck, limiting the ability of professionals and researchers to carry out comprehensive geospatial analyses. Analysts often had to rely on a patchwork of software solutions or custom-built scripts, which could be time-consuming, prone to errors, and not easily reproducible. This piecemeal approach also hindered collaboration and sharing of geospatial analyses and insights.
The importance of overcoming these hurdles cannot be overstated, as geospatial data plays a crucial role in a wide array of critical applications. From urban planning and environmental monitoring to disaster response and global health initiatives, the insights derived from integrated geospatial data are indispensable. It guides decision-makers in policy formulation, business strategy, and scientific research, impacting lives and shaping the future of our societies. As such, the development of a comprehensive tool that can streamline the process of GIS data integration represents a significant leap forward for the field. By providing a standardised, efficient, and robust means to pre-process, clean, unify, and integrate diverse geospatial datasets, such a tool unlocks the full potential of geospatial analysis, facilitating more accurate, insightful, and actionable intelligence from the wealth of data available.
A solution at last: The GIS INTEGRATION R package
Recognizing the critical need for efficient and seamless GIS data integration, a ground-breaking R package, developed by a team of experts: Hossein Hassani (Adjunct Professor at Webster University), Leila Marvian (Lecturer at Imam Reza International University), Sara Stewart (UNECE Consultant), and Steve MacFeely (Director of Data and Analytics at WHO) was recently introduced. The package was rigorously tested using a range of data sources, including a statistical output geography introduced by the Northern Ireland Statistics and Research Agency (NISRA) after the 2021 Census, known as Super Data Zones, alongside other population data from the census. The authors are grateful to NISRA for the availability and quality of their data which proved invaluable to the testing process.
The newly released R package, called GIS INTEGRATION, emerges as a beacon of innovation, meticulously designed to address the multifaceted challenges of GIS data integration. The package is freely available through CRAN, the Comprehensive R Archive Network, which is R's central software warehouse containing an archive of the latest (and previous) versions of R distribution, supporting documents and associated packages for access and download.
Here's a glimpse into the capabilities and benefits of this revolutionary tool:
- Intelligent Pre-Processing: GIS INTEGRATION is equipped with advanced algorithms to perform intelligent pre-processing of two GIS maps, laying the groundwork for accurate integration.
- Advanced Textual Operations: Incorporating techniques such as Lemmatization and Stemming, the package enhances the textual analysis of geospatial data, including the nuanced task of retaining negative prepositions for sentiment analysis.
- Data Cleaning and Standardisation: With functionalities to lowercase variable names, remove punctuation, and trim extra spaces, GIS INTEGRATION ensures your data is clean and uniform, facilitating smoother integration.
- Synonym Finding and Standardisation: The package excels in identifying synonyms and standardizing common names across datasets, a crucial step for linking related but differently labelled data points.
- Seamless Linking of Maps: At its core, GIS INTEGRATION achieves the ultimate goal of seamlessly linking two GIS maps, enabling a unified analysis of combined geospatial datasets.
- Geospatial Analytic and Visualisation: Involves analysing and visualising geographical data, such as location-based information, maps, and GIS systems, to derive insights and make informed decisions across various domains like urban planning, environmental science, transportation, public health, and more.
A milestone for geospatial analysis
The unveiling of the GIS INTEGRATION R package stands as a transformative event in the world of geospatial analysis. This pivotal development represents far more than a mere incremental advancement; it is a paradigm shift that promises to redefine the landscape of spatial data exploration and utilisation.
Geospatial analysis has long been a cornerstone in disciplines ranging from environmental science to urban development, disaster management to public health. However, the potential for innovation and discovery within these fields has often been constrained by the cumbersome nature of integrating complex GIS datasets. The GIS INTEGRATION R package directly addresses this bottleneck, offering a suite of tools that effortlessly melds disparate data sources into a cohesive whole. This tool transcends traditional boundaries by drastically reducing the time and technical expertise required to prepare and harmonise spatial data. Its impact is twofold: it not only amplifies the existing capabilities of seasoned researchers and GIS professionals but also democratises access to sophisticated geospatial analysis for a broader audience. As a result, it facilitates a more inclusive environment where experts and novices alike can contribute to the collective understanding of spatial phenomena.
Next time . . .
We move our focus towards the use of standards to support the integration of statistical and geospatial information, first exploring UNECE's Geospatial View of the Generic Statistical Business Process Model (or GeoGSBPM for short) which describes a range of geospatial-related activities that are needed to produce geospatially-enabled statistics and, crucially, to integrate geospatial information within the statistical process. We hope to see you next time!
This document was produced with the financial assistance of the European Union. The views expressed herein can in no way be taken to reflect the official opinion of the European Union.
The UN Integrated Geospatial Information Framework
The UN Integrated Geospatial Information Framework (UN-IGIF) was developed by UN-GGIM in collaboration with the World Bank as a guide to support governments in the development and strengthening of integrated geospatial information management practices and their inclusion in national plans and strategies. It is also intended to be used as a tool for engagement that will lead to better “coordination, collaboration and coherence across government when working towards strengthening national geospatial information management” (UN-IGIF Part 1 p. 25). The framework was first developed as a means to support and guide lower to middle income countries in the development and strengthening of their own geospatial information management practices and related infrastructures. However, the broader benefits to many high income and developed countries also become apparent as the framework was developed due to its "integrative and inclusive strategic nature" (ibid. p. 1) and it has been applied much more widely than originally intended.
Through an overarching strategic framework, implementation guide, and templates and guides to create and implement country-level action plans, and its seven underpinning principles, eight goals and nine strategic pathways, the framework “creates an enabling environment where national governments can coordinate, develop, strengthen and promote efficient and effective use and sharing of geospatial information for policy formulation, decision-making and innovation” (ibid. p. 9). Both the GSGF and UN-IGIF, by design, allow flexibility to ensure that a range of statistical and geospatial capabilities can be accommodated, which is particularly useful for less-developed countries.
The diagram on the right provides a useful summary of the UN-IGIF and its overall Vision of achieving the efficient use of geospatial information by all countries to effectively measure monitor and achieve sustainable social, economic and environmental development, its Mission for countries to promote and support innovation and provide the leadership, coordination and standards necessary to deliver integration geospatial information management that can be leveraged to find sustainable solutions for social, economic and environmental development, and a wide range of strategic drivers including the 2030 Agenda for Sustainable Development, the Sendai Framework for Disaster Risk Reduction, and the Paris Agreement on Climate Change to name but a few.
The UN-IGIF is also composed of seven underpinning principles, eight goals and nine strategic pathways which are outlined below:
- The seven Underpinning Principles reflect the key characteristics and values that are to guide the implementation of the framework and consist of:
- Strategic enablement
- Transparent and accountable
- Reliable, accessible and easily used
- Collaboration and cooperation
- Integrative solution
- Sustainable and valued
- Leadership and commitment
- Eight Goals have been identified to achieve the framework's overall vision and represent a future state where countries have the capacity and skills to advance decision-making and policy development capabilities through integrated geospatial information management practices. These are:
- Effective geospatial information management
- Increased capacity, capability and knowledge transfer
- Integrated geospatial information systems and services
- Economic return on investment
- Sustainable education and training programs
- International cooperation and partnerships leveraged
- Enhanced national engagement and communication
- Enriched societal value and benefits
- Finally, nine Strategic Pathways have been developed as a means to guide countries in their development of effective geospatial information management and achieve results. As the diagram below highlights, these strategic pathways reflect three broader areas of influence: governance, technology and people, and consist of:
- Governance and institutions
- Legal and policy
- Financial
- Data
- Innovation
- Standards
- Partnerships
- Capacity and education
- Communication and engagement
The strategic pathways are represented as individual pieces of a jigsaw puzzle, each forming an important, interconnected part of the bigger picture; that the framework is successfully integrated and implemented to deliver sustainable social, economic and environmental development where nobody is left behind.
You may remember our previous post on the UNECE Survey that the strategic pathways of the UN-IGIF were used as a means to explore the issues and obstacles to the greater integration of geospatial and statistical data across the UNECE region so their application has a wide scope.
Overview of the vision, mission, strategic drivers, underpinning principles, goals and strategic pathways of the Integrated Geospatial Information Framework (UN-IGIF Part 1 p. 10)
The nine strategic pathways of the Integrated Geospatial Information Framework (based on UN-IGIF Part 1 p. 21)
The UN-IGIF is presented as three separate, though interconnected, parts:
Part 1 takes the form of an Overarching Strategic Framework which presents a comprehensive overview of the UN-IGIF, sharing its key strategic messages and policy drivers. It presents the benefits of the framework, the drivers for change, and barriers to success which need to be overcome. It sets out why integrated geospatial information management is critical to sustainable development, both at national and global levels, particularly focusing on the framework's vision, mission, underlying principles, goals and strategic pathways. The Overarching Strategic Framework is designed to be read by a wide variety of stakeholders, especially decision-makers from institutions and organisations within and across government.
Part 2, the Implementation Guide, is a set of documents which provide specific guidance and detailed information on the actions which should be undertaken when implementing the framework as a means of solving the puzzle. The documents expand on each of the nine strategic pathways, presenting both strategic and operational needs, and sharing important guiding principles, actions, deliverables, outcomes and resources that enable governments to establish "nationally integrated geospatial information frameworks in countries in such a way that transformational change is enabled, visible and sustainable" (UN-IGIF Part 1 p. 8).
Part 3 consists of documentation to support the development of Country-Level Action Plans that operationalise the framework within unique national (and sub-national) contexts, through the provision of specific guides, recommended tasks and templates. Topics include stakeholder identification, a baseline survey, gap analysis, and needs assessment for example. The documents present the purpose of specific tasks and the methods to be undertaken which are clearly outlined in a series of detailed steps. These resources provide an important means to support countries in the preparation and implementation of their own action plans which take account of specific national circumstances and priorities.
Adopting the UN-IGIF has clear benefits
These benefits transcend across the three development pillars of society, the economy and the environment, and will help to address the many challenges we face such as climate change, global health issues, political conflict, and poverty. The UN-IGIF provides a mechanism for countries to take action and bridge the geospatial digital divide for the benefit of all.
Looking ahead
The UN Expert Group on the Integration of Statistical and Geospatial Information (EG-ISGI) has recognised the importance of the UN-IGIF as an enabler to the Global Statistical Geospatial Framework (which was presented in our previous post). The UN-GGIM Decision 12/108 highlighted the importance of leveraging the UN-IGIF for the statistical domain, to strengthen its linkages with the GSGF, and enhance the value that geospatial data can bring to statistical production. As part of their Work Plan 2022 - 2024, the EG-ISGI is currently working to identify a set of actions that expand upon the UN-IGIF for the statistical domain, including the development of a white paper on the subject.
There is also exciting work being undertaken across the European region as James Norris, International Policy Lead at Ordnance Survey (UK) and Chair of the UN-GGIM: Europe Working Group on Integrated Geospatial Information Framework, describes:
In Europe, the UN-GGIM: Europe Working Group on Integrated Geospatial Information Framework has been actively promoting the UN-IGIF within our Region. We were really pleased to be able to participate in the Joint UNECE, Eurostat, UN-GGIM Europe Workshop on Integration of Geospatial and Statistical Data and to see it focusing on the the themes of Effective Governance, Data and Technology, and People and Partnerships. It was also important to hear from Member States on the different ways that they are implementing the UN-IGIF. Looking forward into 2024 our focus is to continue delivering our Regional webinar series. This will build on the webinar An Introduction to the United Nations Integrated Geospatial Information Framework, and will be a more in-depth look at the different methodologies that Member States can use to implement the UN-IGIF, we hope that you will be able to join this discussion. It is also important for us to hear from you about how you are implementing the UN-IGIF and to develop case studies that can be shared. Please do get in touch if you'd like to share your experiences.
With all these activities and support forthcoming, there is never a better time to adopt the UN-IGIF and realise its many benefits!
Next time . . .
We will present an exciting new R package which has recently been developed, allowing users to seamlessly integrate two GIS data sources by pre-processing, cleansing, and unifying the data based on common attributes. This package may solve all your technical problems so won't want to miss this! Until next time!
This document was produced with the financial assistance of the European Union. The views expressed herein can in no way be taken to reflect the official opinion of the European Union.
The Global Statistical Geospatial Framework
At a global level, the 2030 Agenda for Sustainable Development has been a driving force for the greater integration of statistical and geospatial data as it requires robust, harmonised data at granular levels of geography for the production and monitoring of SDG indicators. In support of the 2030 Agenda, the Population and Housing Censuses, and other important development initiatives ranging from local to global levels, UN-GGIM published the Global Statistical Geospatial Framework (GSGF) in 2019 as a key policy framework to act as a “bridge between statistical and geospatial professional domains, between NSOs [National Statistical Organisations] and NGIAs [National Geospatial Information Agencies], and between statistical and geospatial standards, methods, workflows and tools” (GSGF, p. 6). By applying the framework's five Principles and four Key Elements, the production of high-quality "harmonised, standardised and geospatially-enabled statistical data" (ibid., p. vii) can be realised. Such data plays a valuable role in informing, supporting and driving evidence-based decision-making and policy development across all geographic scales.
The GSGF is clearly summarised in this useful (and, by now, very famous) diagram shown to the right. It comprises of:
- Geospatial and statistical data Inputs
- Five Principles which outline broad processes to enable statistical and geospatial data integration and work through a hierarchical "bottom-up" approach:
- Use of fundamental geospatial infrastructure and geocoding
- Geocoded unit record data in a data management environment
- Common geographies for the dissemination of statistics
- Statistical and geospatial interoperability
- Accessible and useable geospatially enabled statistics
- Four Key Elements which facilitate the application of the five Principles:
- Standards and Good Practice
- National Laws and Policies
- Technical Infrastructure
- Institutional Collaboration
- Resulting Outputs which stem from the GSGF processes and provide “a higher degree of structural harmonisation and standardisation, as well as geospatial flexibility, . . . [and] have an inherently greater capacity for integration based on location and a substantially greater capacity to be further used in more complex statistical data integration” (ibid. p. 8).
Overview of the inputs, principles, key elements and outputs that form the Global Statistical Geospatial Framework (GSGF, p. 5)
The GSGF is presented as two separate, but complementary, documents:
The Global Statistical Geospatial Framework itself as the main policy document which presents the context and key concepts of the framework. It is already available in six different languages (English, Arabic, French, Mandarin, Portuguese and Spanish) enabling its broad use. The information is presented in three very easy-to-digest parts:
- Part 1 presents the GSGF as a high-level overview of the framework, outlining its Inputs, Principles, Key Elements and Outputs. It is designed to draw the reader in by presenting key information on the framework, highlighting the importance of integrated data and the means to achieve integration.
- Part 2 goes into more detail on each of the five Principles, addressing the need for each Principle, what is covers, the main objective of its use, the requirements and benefits, the relationship to other principles, the data inputs required and the key stakeholders involved.
- Part 3 provides additional supporting information in the form of three annexes, including definitions of key terms, further information on the need to use internationally-adopted standards and the importance of assessing data quality across all stages of the framework, and further reading and resources on other national and international frameworks, standards, and privacy and data disclosure prevention.
The Global Statistical Geospatial Framework: Implementation Guide as an important supporting document which provides detailed guidance on how to implement the GSGF. It acts as a living document which will be periodically updated to include best practices, developments and innovations in the field. It consists of three main sections:
- Implementation guidance on four key areas that are seen as critical to successfully implementing the GSGF: geocoding, common geographies, fostering interoperability, and ensuring privacy and confidentiality. For each area, the relevant GSGF Principles are presented, the concept is defined, its importance highlighted, how it can be implemented is described, and further reading and relevant resources are shared.
- Terminology related to the integration of statistical and geospatial information is then presented as a means to improve understanding and the adoption of common definitions across the framework and its users.
- Experiences of implementing the GSGF are then presented from 30 different countries (including Australia, Cuba, Germany, Indonesia, and Senegal) and five regions (Africa, the Americas, Asia and the Pacific, Europe and Western Asia). The case studies discuss the level of overall implementation of the GSGF, share more detail on the implementation of each of its five Principles, and highlight the value of the GSGF to national- and regional-level responses to COVID-19 as a high-impact use case.
GSGF Europe: Adapting the GSGF to the European context
The GSGF has been described as "a framework for the world" and its concepts and requirements are broad enough to be applied to differing regional contexts. Within Europe, the European Cohesion Policy 2021-2027, which aims to correct imbalances between countries and regions in order to strengthen social, economic, and territorial cohesion across the EU, requires detailed and harmonised data across different spatial scales of analysis and geospatial data is already often used in conjunction with regional statistical data in various phases of the policy-making process (e.g. Territorial Impact Assessments). The INSPIRE Directive has also established an Infrastructure for Spatial Information in the European Community (INSPIRE) to “create a European Union spatial data infrastructure for the purposes of EU environmental policies and policies or activities which may have an impact on the environment . . . [to] enable the sharing of environmental spatial information across Europe and assist in policy-making across boundaries” (European Commission). Other important initiatives, such as the GEOSTAT projects led by Eurostat and the European Forum of Geography and Statistics (EFGS), have been working towards the greater integration of statistical and geospatial data across the EU through the development of common guidelines for grid-based and geospatial statistics for use by national statistical and geospatial organisations. Of significance here, the GEOSTAT 4 project has conceptualised and interpreted the GSGF within the European context to support its implementation at a regional level, resulting in the GSGF Europe guidance document, an associated User Guide, and a range of other supportive resources available on the GEOSTAT Information Service.
The GSGF Europe provides a "high-level summary of the conceptualisation and interpretation of the GSGF in the European context", supporting the global framework's regional implementation by adopting it to the European statistical and geospatial operating environment. The document consists of three main sections:
- Key aspects of the GSGF and its five Principles are first interpreted for the document and the relationship between the principles are highlighted.
- The GSGF is then examined within the context of the European operating environment, a GSGF Europe Reference Architecture is defined (as the basic structure and operation of the European statistical and geospatial community), the GSGF's four Key Elements are interpretated, and four topics for future enhancement are presented: quality, data collection, confidentiality and innovation.
- Finally, nine relevant statistical and geospatial frameworks which are actively applied in Europe are presented, with the authors recognising that the GSGF "is part of a family of frameworks that aim to integrate data and information" (GSGF Europe p. 5) that are complementary and should not be considered in isolation.
An important outcome of the GEOSTAT 4 project is the development of a set of Requirements and Recommendations which break down the framework into a series of small, concrete and management steps that enable the GSGF to be implemented more consistently and systematically across Europe. The diagram to the right below summarises these requirements and recommendations, but if you would like to look at them in more detail, you can access them here: Requirements and Recommendations | EFGS.
Requirements and Recommendations to support the implementation of the GSGF in Europe (GSGF Europe p. 60)
The GSGF in Finland project: Interpreting the GSGF within a national operating environment
Contributions by Mervi Haakana (Statistics Finland), Rina Tammisto (Statistics Finland) and Panu Muhli (National Land Survey of Finland).
We end this blog by sharing an exciting new EU-funded project, the GSGF in Finland—Integration of geospatial and statistical information in Finland project (or GSFI for short), which is currently being undertaken by Statistics Finland, the Finnish Environment Institute and the National Land Survey of Finland who are working in close cooperation with the National Network on Integration of Statistics and Geospatial Information in Finland. The project began in February 2023 and is taking place over a period of two years.
The project will interpret the GSGF and the GSGF Europe within the Finnish operating environment in order to gain a common understanding of the current and target state of integrating geospatial and statistical information in Finland as well as its development goals. To achieve this, an analysis of the current state and a target state architecture will be undertaken, the development needs defined, and the benefits of the GSGF model will be identified and described.
The structure of the work taking place in the GSFI project is outlined in the diagram to the right.
Through the project, it is hoped that the following goals will be realised:
- Data from a range or sources and types for multiple purposes are easy to use and analyse in different geographies.
- Statistics are geospatially enabled.
- Geospatial statistics are nationally and internationally interoperable.
- The geospatial production solutions make information production more efficient.
- Stakeholders have a common understanding of the situation and direction.
- The project outputs will be shared not only nationally, but also in the Nordic countries and more widely.
Structure of the work being undertaken during the GSFI project
There is a lot of value in adapting the GSGF to the Finnish context, as Mervi Haakana from Statistics Finland describes:
The focus of this project and the value of its results is to understand the theoretical models in practice and connected to the national policy and operating environment. Already at this stage of the work, examining different perspectives of the GSGF and GSGF Europe in our own environment has proven to be important. Even translating part of the text (not all) into Finnish has led to discussions and new understanding about the framework. One aim is also to bring the ability to share responsibilities and concrete tasks between organisations and to identify mutual processes. We also hope that the project results will serve as a valuable benchmark for other countries.
It is clear that the GSFI project is already achieving some great results and we look forward to hearing more as the project progresses! We also hope that the GSFI project will inspire you to embark on your own journeys towards successfully implementing the GSGF.
Adopting the GSGF will bring many benefits . . .
. . . so why wait to get started?
Next time . . .
We will take a look at the UN Integrated Geospatial Information Framework, another key policy framework relating to data integration. Hopefully see you then!
This document was produced with the financial assistance of the European Union. The views expressed herein can in no way be taken to reflect the official opinion of the European Union.
Attendance
The workshop was attended by over 60 representatives from National Statistical Institutes (NSIs), National Mapping and Cadastral Agencies (NMCAs), intergovernmental organisations and private sector organisations, with 28 different countries represented from across the UNECE region, spanning from the United States of America in the west as far as Kazakhstan in the east.
The UNECE Member States in attendance were: Albania, Armenia, Austria, Belgium, Bosnia and Herzegovina, Finland, France, Georgia, Germany, Ireland, Italy, Kazakhstan, Kyrgyzstan, Malta, Moldova, the Netherlands, North Macedonia, Norway, Poland, Portugal, Serbia, Slovakia, Slovenia, Sweden, Switzerland, Ukraine, United Kingdom, and the United States of America. The workshop was also attended by representatives from EuroGeographics, Eurostat, the OECD, UN-GGIM: Europe, UNECE, UNHCR, the World Bank Group, and Esri. Such broad representation and expertise really made the event such a success and we are extremely grateful for the efforts that participants made to attend the workshop and the (sometimes considerable) distances that were travelled to get there!
This document was produced with the financial assistance of the European Union. The views expressed herein can in no way be taken to reflect the official opinion of the European Union.
What did the UNECE Survey reveal?
The chart to the left shows the overall respondent rating of the degree of impact that each UN-IGIF strategic pathway had on their organisation's ability to progress activities to integrate statistical and geospatial data. For the purpose of this blog post, we will focus on the top three strategic pathways which were rated as having the highest impact on data integration. These are:
1. Financial
2. Communication and Engagement
3. Data & Technical Infrastructure
Financial issues were rated as having the highest impact on data integration in both target and non-target countries, as well as in National Statistical Institutes (NSIs), however, respondents from National Mapping and Cadastral Agencies (NMCAs) considered that communication and engagement issues had the bigger impact which should be noted.
We will now dig a bit deeper and discuss some of the reasons behind these ratings.
So, where do we go from here?
This blog post has focused on the top three strategic pathways which were rated as having the highest impact on data integration within the UNECE Survey, although there are also other wider issues at play. While much work has been undertaken to support the greater integration of geospatial and statistical information, more must be done to embed data integration activities within business-as-usual practices in a comparable and consistent fashion across the UNECE region. There are a range of multi-dimensional issues and obstacles still to be overcome, given the wide variance in national governance frameworks, laws and policies, the ability to access adequate and sustainable financial resources, the level of cooperation with other national and international bodies, the adherence to wider policy frameworks and common standards, the ability, skills and capacity to innovate, and effectively communicate the need for data integration activities and their associated benefits to both decision-makers and the wider user community.
In light of the issues and obstacles explored in this blog post, some recommendations can be made:
1. Identify and promote sustainable funding resources and models to support data integration activities at national levels.
2. Enhance communication and engagement strategies to grow awareness of the benefits of data integration and better support the sharing of best practice and new technologies.
3. Promote greater data standardisation and interoperability through the use of harmonised standards, operating models, production processes and services.
These recommendations could support and complement other key recommendations made by UNECE, Eurostat and others in the field of data integration and, in their adoption, may provide a driving force for change so that the value of data integration is fully realised and data of sufficient quality, accessibility, currency, reliability and granularity is produced consistently to protect people, the planet, prosperity, peace and partnerships so that “no one will be left behind” (United Nations).
This document was produced with the financial assistance of the European Union. The views expressed herein can in no way be taken to reflect the official opinion of the European Union.
Images in this blog were sourced from Flaticon.com.
So, why explore collaboration and partnerships?
As Isaac Newton famously said:
"If I have seen further it is by standing on the shoulders of giants."
Partnerships, in other words, the strategic alliance of two or more parties who agree to cooperate to advance their shared interests and achieve common goals, have long been viewed as key tools of effective governance. Some partnerships may focus on the delivery of local initiatives at national levels, developing or adapting policy frameworks to better suit the needs of local societies and economies. Other partnerships may seek to coordinate broad policy areas at regional and international scales. But in all cases, successful partnerships are centred around collaboration, drawing on the unique skills that each partner brings to their alliance in order to create new value together (see Collaborative Advantage: The Art of Alliances). At a time when rapid technological change, growing economic and political uncertainty, mounting concerns for the environment and the impacts of climate change, and the effects (whether direct or indirect) of the COVID-19 pandemic transcend national and regional boundaries, effective strategic partnerships can offer valuable contributions to sustainable development and the delivery of innovative, inclusive, targeted, and cost-effective solutions to benefit society.
The strategic partnerships and collaborative activities in place across the statistical and geospatial sectors (as outlined in our earlier post on Data Integration: Key players and recent developments) are strong, long-standing and of benefit to the data integration agenda. Eurostat has observed that statistical and geospatial data integration is growing rapidly in some European countries due to close cooperation between national statistical and geospatial organisations. The European Committee of the Regions further notes that “pan-European interoperability in most fields is still a future goal, however, good progress has been made in particular by several phases of the GEOSTAT projects also regarding the establishment of cooperation between institutions and the integration of spatial and statistical data”. PARIS21, as a global partnership of experts and policymakers in statistics, has also identified that governments in many low-income countries are already implementing multi-stakeholder approaches to progress statistical and geospatial data integration which is very promising. It is, however, important that the international and regional partnerships already in place, some of which are undertaking similar activities relating to data integration, work together to ensure that their workstreams are aligned, and not duplicated, so there is a clear overarching voice that transcends across the different policy frameworks and guidelines that national statistical and geospatial organisations are encouraged to adopt. At national levels, the traditional separation of statistical and geospatial organisations has historically hampered efforts to collaborate with each other, although this is now changing with many good examples of national collaboration in practice (more on that in a later post).
What did the UNECE Survey find out?
In light of the importance of effective collaboration and partnership arrangements to support activities to integrate statistical and geospatial data, the UNECE Survey asked respondents a series of questions to understand the level of involvement in wider activities relating to data integration at both national and international levels. Some key findings are presented below.
- Survey respondents were asked how closely they worked with their national statistical or geospatial counterpart and most respondents noted that their organisations were separate but closely linked (61%).
- Only 9% of respondent organisations were fully integrated with their statistical or geospatial counterpart.
- These patterns were broadly reflected across both target and non-target country organisations.
- Most respondents (67%) had a cooperation agreement in place with their national statistical or geospatial counterpart which suggests that there is a relatively good level of cooperation at national levels.
- Target country organisations had a marginally lower level of cooperation (60%) than non-target countries (69%).
- While the form and type of cooperation varied from country to country, ranging from legal obligations to ad hoc meetings, the most common cooperation mechanisms consisted of data sharing agreements, memorandums of understanding, and bespoke agreements (e.g. service level agreements).
- Several organisations are actively working on the development of national cooperation mechanisms to strengthen their governance frameworks, the exchange of information, and the ability to integrate statistical and geospatial information.
These snapshots from the survey indicate that while the overall level of participation in regional and international activities related to geospatial and statistical data is good overall, as is the breadth and variety of the working groups attended, more needs to be done to explore why levels of engagement from target countries are significantly lower and determine how this can best be remedied. Respondents highlighted the importance of established and agreed collaboration through multilateral partnerships as well as the need for build greater awareness about the strength of partnerships and cooperation amongst different data providers that ensure that reliable, objective, accurate and consistent data can be produced, shared and integrated.
This document was produced with the financial assistance of the European Union. The views expressed herein can in no way be taken to reflect the official opinion of the European Union.
Firstly, why look at the use of data and technology?
Well, on a global scale, society is becoming ever more data-driven with more than 2.5 quintillion bites of data being generated every day (which is quite something)! The availability of quality data that is accurate, comprehensive, at an appropriate level of detail and temporality, and from verifiable and authoritative sources, is critical for evidence-based decision-making and policy development across all levels. Data plays a central role in the 2030 Agenda and the ability to fully measure and monitor progress on the SDGs. Not only is the quality of data important, but also the strength of the technical infrastructure which underlies its creation, management, use, and dissemination within and across organisations. A strong data infrastructure will ensure better efficiency and productivity of its users, ease of collaboration between different groups, and securely managed access to organisational data for both internal and external users. By utilising appropriate digital technologies and methodological frameworks to collect, analyse and interpret data, real actionable insights can be obtained. Yet, these benefits have not yet been fully realised in a consistent way as the World Bank notes: “Even as new technology makes more data and wider uses of data possible, there are still many blank spaces on the global data map”. While both the quality and availability of data has been growing over recent years, in general, it is considered that “statistical capacity still needs strengthening and data literacy must be enhanced at all levels of decision-making” which will “require coordinated efforts on the part of data producers and users from multiple data systems" (UN Statistics Division).
The quality and accessibility of statistical and geospatial data, and the strength of the technical infrastructure that supports it throughout its lifecycle, is central to the data integration agenda. At a global level, it has been recognised that advances in the integration of statistical and geospatial data have "benefitted from the availability of powerful geospatial tools that enhance the value and usability of official statistics by leveraging the application of the spatial context" (PARIS21). The GEOSTAT 4 / GISCO survey also revealed that around 50% of the countries surveyed reported that they had a strong and sustainable data infrastructure that could support the integration of statistical and geospatial information. The INSPIRE Directive also brought the importance of metadata, and its uniform structure, to the fore in the management of spatial datasets, providing definitions and lists of categories to describe the content, data type, and usage. As UNECE have highlighted, there is also the “prior existence of flexible frameworks for the modernisation of official statistics that can be adapted to include geospatial information with little impact on the existing organisational structure”. For example, UNECE’s Generic Statistical Business Process Model (GSBPM) has recently been enhanced to include a geospatial perspective, appropriately termed GeoGSBPM. We will be discussing the GeoGSBPM in more detail in a later post. From these few examples, it is clear that good progress has been made at global and regional scales to highlight and support the development and maintenance of high-quality data and robust technical infrastructures, but issues still remain which hinder the greater integration of statistical and geospatial information at national levels.
So, what did the UNECE Survey discover?
Recognising the central role that data and technology play in the integration of geospatial and statistical information, the UNECE Survey asked respondents a number of questions relating to their organisational use of data and technology. Some highlights are presented below:
- Most respondents from National Statistical Institutes (NSIs) often (53%) or always (18%) used geospatial data within their workflows.
- Only one NSI respondent never used geospatial data in their workflows.
- A lower proportion of NSI respondents from the project's target countries (located in Eastern Europe, the Caucasus and Central Asia) always or often used geospatial data within their workflows (45%) in comparison to non-target countries (79%).
- Respondents noted a broad range of uses for geospatial data within statistical processes, with the most common relating to census operations, geocoding, spatial analysis, and dissemination activities. Several respondents also discussed their production of grid statistics, particularly in relation to population and age information.
- An overwhelming majority (84%) of NSI respondents have, or are planning to incorporate, geospatial data within the 2020 census round.
- The proportion of NSIs using geospatial data within their census activities was much lower in target countries (55%) than non-target countries (94%).
- The most common uses of geospatial data within census operations related to the geocoding of address data for building and dwelling registers, the production of enumeration areas, the monitoring of data collection and census progress, and the creation and dissemination of grid statistics (primarily at the 1 kilometre-squared grid level but as high as 100 metres-squared).
- A slight majority of respondents from National Mapping and Cadastral Agencies (NMCAs) often (50%) or always (5%) used statistical data in their workflows which is much lower than the converse reported by NSIs (as above).
- 28% of NMCA respondents never used statistical data in their workflows which is much higher than the converse reported by NSIs.
- A higher proportion of NMCA respondents from target countries always or often used statistical data (75%) than from non-target countries (50%).
- Common uses of statistical data within geospatial activities included within data production and management processes, thematic map production (particularly using population and census data), and spatial analysis using demographics and deprivation indices to inform policy development and emergency preparedness and response.
- All respondents, whether NSI or NMCA, had access to some form of GIS software, with the most popular being Esri ArcGIS software (37%) followed closely by open-source QGIS software (34%), and then other more bespoke or internally-developed software applications and packages (22%).
- The vast majority of respondents (with the exception of three organisations) had access to one or more statistical software packages, the most common being Microsoft Excel (28%), R (20%) and Python Statistics Libraries (15%).
These highlights from the survey suggest that organisations who responded to the survey are integrating geospatial/statistical data within their workflows and have a good level of access to relevant software to support such tasks. It is clear, however, that there are some disparities in the extent of data integration activities between NSIs and NMCAs and, similarly, between target and non-target countries. In a later post, we will share some of the issues and obstacles relating to data and technology which were highlighted by respondents to the survey.
This document was produced with the financial assistance of the European Union. The views expressed herein can in no way be taken to reflect the official opinion of the European Union.
In the first post of this mini-series, we will introduce you to the project and provide some background and context to the UNECE Survey. Are you ready to find out more? Let's go!!
So, tell me more about your EU-funded project to develop capacity in geospatial and statistical data integration . . .
As we outlined in our first post (Welcome to INGEST), the role of integrated data as a driver for evidence-based decision-making has never been more important and has been brought to the fore by the 2030 Agenda and its call for data that is accurate, current and of high-resolution to measure and monitor the achievement of its Sustainable Development Goals. In our previous post (Key players and recent developments) we also discussed how global efforts to drive the greater integration of statistical and geospatial data have been going on for a decade and many great outcomes have been achieved, however, the benefits have not yet been fully realised consistently across the UNECE region due a to range of complex but interconnected reasons (which we will discuss in a later post).
Recognising the potential for growth, the European Commission has funded a 21-month project, currently being led by UNECE, to develop greater capacity in statistical and geospatial data integration across the UNECE region to foster stronger links between the two communities, support greater collaboration and encourage greater data integration through the promotion of stronger institutional partnerships and the adoption of common standards. The project is supporting existing activities to strengthen the integration of statistical and geospatial information by Eurostat, UN-GGIM: Europe and others, and has a particular focus on sixteen selected target countries in Eastern Europe, the Caucasus and Central Asia.
A number of key activities are being undertaken as part of the project including (amongst other things):
- Issuing an online survey to gain stakeholder insights on data integration (more on that below).
- Organising a Joint UNECE / Eurostat / UN-GGIM: Europe Workshop on Integrating Statistical and Geospatial Data which will take place in Belgrade, Serbia on the 4-5 October 2023.
- Establishing a UNECE-led task force on standards issues relating to data integration.
- Creating supportive material on data integration including a UNECE wiki space, this blog series, and other documentation.
By carrying out these activities, the project hopes to:
- Increase awareness of the need for more integration of geospatial and statistical data, especially within the project's target countries.
- Develop a better understanding of the limitations of current geospatial and statistical data standards in the context of data integration.
- Improve collaboration between the geospatial and statistical communities based on greater mutual awareness and understanding.
Next time . . .
We will present more results from the UNECE Survey in the second part of our mini-series which will focus on the organisational use of geospatial and statistical data and technology. See you then!
This document was produced with the financial assistance of the European Union. The views expressed herein can in no way be taken to reflect the official opinion of the European Union.
So, who are the key players in the quest for greater data integration?
Global efforts to drive the greater integration of geospatial and statistical data have been going on for more than a decade and have been centred on the work of the United Nations and its various divisions and bodies, particularly the UN Statistics Division and the UN Committee of Experts on Global Geospatial Information Management (UN-GGIM). From this global stage, data integration activities have been increasingly extended and adapted to different regional contexts. In Europe, for example, this work is led by four key players: UNECE, Eurostat, UN-GGIM: Europe, and the European Forum for Geography and Statistics. There are also great examples of data integration activities within the national statistical and geospatial organisations which are supporting other countries who are not so advanced to their data integration journeys.
The key players, at international, regional and national levels, are outlined in the diagram below:
A summary of each of the main organisations and bodies is outlined in the table below. If you would like to find out more, please click on the links provided.
Economic and Social Council (ECOSOC) | One of the six main bodies of the United Nations whose role is to advance the three elements of sustainable development - the economy, society and the environment. It is described as a "central platform for fostering debate and innovative thinking, forging consensus on ways forward, and coordinating efforts to achieve internationally agreed goals". |
United Nations Statistical Commission (UNSC) | A functional commission of ECOSOC which forms the highest decision-making body for international statistical activities and oversees the work of the United Nations Statistical Division (UNSD). It is responsible for the "setting of statistical standards and the development of concepts and methods, including their implementation at the national and international level". |
United Nations Economic Commission for Europe (UNECE) | One of five regional commissions established by ECOSOC whose main aim is to promote pan-European economic integration. It includes 56 member states from across Europe, North America and Asia and over 70 international professional organisations and non-governmental organisations are involved in UNECE activities. |
UNECE Statistical Division | UNECE's Statistical Division helps national statistical systems meet their data requirements for the 2030 Agenda through the provision of methodological guidance, modernisation activities and capacity development. It brings together experts from across the statistical community to "promote efficiencies and innovative ways to tackle persistent and emerging challenges in official statistics". |
Conference of European Statisticians (CES) | CES brings together leading statisticians from over 60 countries to drive statistical work through the provision of guidelines and recommendations, the setting of standards for statistical production, the global assessment of national statistical systems, and the completion of in-depth reviews to identify and respond to emerging issues. UNECE provides the Secretariat to CES. |
United Nations Committee of Experts on Global Geospatial Information Management (UN-GGIM) | The leading intergovernmental body regarding the use of geospatial information, acting as a forum for coordination, decision-making and setting direction for the production, accessibility and use of geospatial information within global, regional and national policy frameworks. |
UN-GGIM: Europe | One of five regional committees which operates within the broader scope of UN-GGIM whose role is to identify European issues relevant to geospatial information management and recommend necessary actions to maximise the economic, social and environmental benefits of European geospatial information management. |
United Nations Department of Economic and Social Affairs (UN DESA) | An overarching body which upholds the development pillar of the United Nations, is guided by the 2030 Agenda, and is home to the SDGs. It provides intergovernmental support and capacity development work and is described as the "think tank of the UN", generating, analysing and compiling a wide range of data and statistics on related themes that enable Member States to assess and tackle common social, economic and environmental problems. |
United Nations Statistics Division (UNSD) | Sits within UN DESA with the aim to advance the global statistical system by compiling and sharing global statistical information, developing standards and norms for statistical activities, supporting countries in the strengthening of national statistical systems, and coordinating international statistical programmes and activities. |
European Commission | The European Commission (EC) is part of the executive of the European Union (EU) whose role is to help shape the overall strategy of the EU, develop new EU legal and policy frameworks, monitor their implementation, and manage the EU budget including associated funding programmes. It also plays a central role in international relations, supporting international development and the delivery of aid. |
Eurostat | The statistical authority of the EU, providing high-quality statistics and data on Europe in partnership with national statistical institutions and other bodies across Europe through the mechanism of the European Statistical System (ESS). It coordinates the statistical activities of the ESS to ensure the quality and consistency of data in accordance with the European Statistics Code of Practice. Eurostat has also been progressing the statistical and geospatial data integration agenda through activities relating to GISCO, the Geographic Information System of the Commission. |
European Forum for Geography and Statistics (EFGS) | Set up as a voluntary cooperation between National Statistical Institutions (NSIs) in the Nordic countries in 1998, but has expanded to over 40 states and territories, and focuses on the development of best practices in the production of geostatistics in Europe and is home to the GEOSTAT projects (more on that below). |
What about recent developments in the field of data integration?
Activities to progress the greater integration of geospatial and statistical data have been going on for more than a decade and some of the highlights are provided below.
At a global level:
- UN-GGIM's Expert Group on the Integration of Statistical and Geospatial Information whose role is to raise awareness and promote the importance of integrated statistical and geospatial information to support decision-making and policy development across all political levels. Their work includes the development of the Global Statistical Geospatial Framework which was adopted by the Committee of Experts at their ninth session as a bridge to facilitate the integration of a range of data from both the statistical and geospatial communities. At their tenth session, the Committee of Experts also adopted the United Nations Integrated Geospatial Information Framework to assist countries in the development and enhancement of their own geospatial information management processes. We will delve into these frameworks in more detail in later posts.
- The Global Forum for Geography and Statistics (GFGS) which acts as a global network on geography and statistics to present, share and discuss new ideas and best practice relating to geospatial and statistical data. The GFGS, in collaboration with UNECE and EFTA, currently run a series of coffee talks. See here for more information including details on upcoming talks.
At a regional level:
- UN-GGIM: Europe's Working Group on Data Integration which focuses on the integration of geospatial data with other information including statistical data, and is currently running webinar series on data integration. See here for upcoming events.
- Eurostat's activities relating to GISCO (the Geographic Information System of the COmmission) which includes coordinating Commission-wide geographic information activities, promoting the use of geospatial data within the European Statistical System, chairing a working group on the integration of statistical and geospatial information, and overseeing annuals funding calls for project proposals relating to data integration.
- The European Forum for Geography and Statistics (EFGS) who have worked in collaboration with Eurostat on the GEOSTAT Projects which have focused on the development of common guidelines for grid-based and geospatial statistics for use by national statistical and geospatial organisations to promote the greater integration of statistical and geospatial data across the EU. The GEOSTAT 4 project has conceptualised and interpreted the Global Statistical Geospatial Framework within the European context, publishing GSGF Europe in 2021.
- UNECE's High-Level Group for the Modernisation of Official Statistics (HLG-MOS) whose role is to advance the modernisation of official statistics. They have published a Guide to Data Integration for Official Statistics as well as a Geospatial View of Generic Statistical Business Process Model (GeoGSBPM). UNECE has also recently embarked on a new project to produce internationally agreed guidance for the next round of censuses in 2030 under a number of key themes including technology, looking at GIS data and related approaches, and geospatial information and small area statistics for censuses which will further promote the data integration agenda within a global update of international guidance for censuses. See here for more information.
Next time . . .
We will present some results from the recent UNECE Survey on the Integration of Statistical and Geospatial Information which was undertaken as part of an EU-funded project to develop capacity in geospatial and statistical data integration across the UNECE region. More on the project and the survey results soon!
This document was produced with the financial assistance of the European Union. The views expressed herein can in no way be taken to reflect the official opinion of the European Union.
Why is data integration important?
Wow, I can definitely see the value of integrating geospatial and statistical data. So, what more can I learn?
This blog series will explore a range of topics relating to data integration and take a deep dive into some of the guidance, resources and best practice on the integration of geospatial and statistical data. Next time, we will introduce you to the key players working the field of data integration and bring you up to speed on some recent developments. We hope to see you then!